Precise static happens-before analysis for detecting UAF order violations in android

© 2019 IEEE. Unlike Java, Android provides a rich set of APIs to support a hybrid concurrency system, which consists of both Java threads and an event queue mechanism for dispatching asynchronous events. In this model, concurrency errors often manifest themselves in the form of order violations. An order violation occurs when two events access the same shared object in an incorrect order, causing unexpected program behaviors (e.g., null pointer dereferences). This paper presents SARD, a static analysis tool for detecting both intra-and inter-thread use-after-free (UAF) order violations, when a pointer is dereferenced (used) after it no longer points to any valid object, through systematic modeling of Android's concurrency mechanism. We propose a new flow-and context-sensitive static happens-before (HB) analysis to reason about the interleavings between two events to effectively identify precise HB relations and eliminate spurious event interleavings. We have evaluated SARD by comparing with NADROID, a state-of-the-art static order violation detection tool for Android. SARD outperforms NADROID in terms of both precision (by reporting three times fewer false alarms than NADROID given the same set of apps used by NADROID) and efficiency (by running two orders of magnitude faster than NADROID)

Event trace reduction for effective bug replay of Android apps via differential GUI state analysis

© 2019 ACM. Existing Android testing tools, such as Monkey, generate a large quantity and a wide variety of user events to expose latent GUI bugs in Android apps. However, even if a bug is found, a majority of the events thus generated are often redundant and bug-irrelevant. In addition, it is also time-consuming for developers to localize and replay the bug given a long and tedious event sequence (trace). This paper presents ECHO, an event trace reduction tool for effective bug replay by using a new differential GUI state analysis. Given a sequence of events (trace), ECHO aims at removing bug-irrelevant events by exploiting the differential behavior between the GUI states collected when their corresponding events are triggered. During dynamic testing, ECHO injects at most one lightweight inspection event after every event to collect its corresponding GUI state. A new adaptive model is proposed to selectively inject inspection events based on sliding windows to differentiate the GUI states on-the-fly in a single testing process. The experimental results show that ECHO improves the effectiveness of bug replay by removing 85.11% redundant events on average while also revealing the same bugs as those detected when full event sequences are used